A short and quick presentation on predicting ligand binding sites which include four methods for prediction binding sites.First go through the references and then quick look at this presentation really helpful to you. Enjoy

1. PREDICTION OF LIGAND BINDING
SITES
Amit Singh
Bioinformatician
Central University of Punjab
http://www.ceitec.eu/ceitec-mu/protein-structure-and-dynamics/rg1Weisel,M. et al. (2007) PocketPicker: analysis of ligand binding-sites with shape
descriptors. Chem. Cent. J., 1, 7.

2. Ligand Binding Sites
 These are the sites of activity in proteins
usually lie in cavities.
 Binding of substrate typically serves as a
mechanism for triggering some events like
chemical modification or conformational
change.
 The size and shape of these cavities
command the three dimensional geometry
of ligands.
 Cavities determination is prerequisite for
protein ligand docking, structure-based
drug design.
•J. Yu, Y. Zhou, I. Tanaka, M. Yao, Roll: A new algorithm for the detection of protein pockets and cavities with a rolling
probe sphere. Bioinformatics, 26(1), 46-52, (2010)

3. Methods for prediction of ligand binding sites.
PocketPicker
PASS.
Roll
LIGSITE

4. PocketPicker.
5.
Preparation of shape descriptors to enable comparisons of different pocket shapes.
4.
Clustering of adjoining grid probes(BI 16-26) indicating buried regions of the structure to find potential binding-sites.
3.
Calculation of buriedness values of grid probe installed in areas closely above the protein surface.
2.
Grid points that exceed maximal distance of 4.5A
o
to the closet protein atom are excluded.
1
A rectangular grid with 1A
o
mesh size is generated around the protein.

6. Shapes of pocket conformation by PocketPicker.

7. PASS(Putative Active Sites with Spheres)

8. Schematic illustration of Roll: Slice of the grid system.
Jian Yu et al. Bioinformatics 2010;26:46-52
Roll

9. Volume depth.
Jian Yu et al. Bioinformatics 2010;26:46-52

10. LIGSITE
1.
Protein is projected onto a 3D grid and grid points are labelled as
protein,surface,solvent.
2.
Sequence of grid points starts and ends with surface grid points
and which has solvent grid point in between is identified.
3.
Number of surface -solvent-surface event of each solvent grid is
recorded.
4.
A minimum threshold for surface -solvent-surface event is applied
to solvent grid to mark them as pocket.
5.
Clustering of pocket grid points and ranked by no. of grid points.

12. References
 Brady GP, Stouten PFW: Fast prediction and visualization of protein binding pockets
with PASS. J Comput-Aided Mol Des 2000, 14:383-401.
 Weisel,M. et al. (2007) PocketPicker: analysis of ligand binding-sites with shape
descriptors. Chem. Central J., 1, 7–23.
 Jian Yu, Yong Zhou, Isao Tanaka: Roll: a new algorithm for the detection of protein
pockets and cavities with a rolling probe sphere. Bioinformatics, (2010) 26(1):46-52.
 Huang,B. and Schroeder,M. (2006) LIGSITEcsc: predicting ligand binding sites using
the Connolly surface and degree of conservation. BMC Struct. Bio., 6, 19.